Applied Econometrics: Pooled Cross-Section Analysis in R

Understanding how policy changes affect outcomes requires robust statistical methods. Pooled cross-section analysis is a foundational technique for measuring these impacts. This course provides a complete, hands-on guide to performing practical econometric analysis using the R programming language. You will move from defining fundamental concepts to executing complex regression models, ensuring your analysis is both rigorous and reproducible. What you'll learn: * Learn the theoretical foundations of pooled cross-section data and when this methodology is appropriate for policy evaluation. * Practice setting up and cleaning real-world datasets for econometric modeling using R. * Master the estimation and interpretation of Ordinary Least Squares (OLS) models on data structured across time. * Apply the Difference-in-Differences (DiD) method to accurately measure the causal effects of policy interventions. * Understand how to calculate and report robust standard errors in the context of pooled and panel data. The course begins with essential terminology and data manipulation techniques in R. We then systematically explore model specification, estimation, hypothesis testing, and the critical interpretation of policy effects using practical, reproducible code snippets. This course is designed for beginners in econometrics or statistical programming who want to apply foundational regression techniques using R. No prior experience with R or advanced statistics is required. Start building your practical econometrics skills today.